Data Scientist
Posted: 2 August, 2022Organization: East West Bank
Location: New York, NY
Introduction:
Since 1973, East West Bank has served as a pathway to success. With over 120 locations across the U.S. and Greater China, we are the premier financial bridge between the East and West. Our teams of experienced, multi-cultural professionals help guide businesses and community members on both sides of the Pacific looking to explore new markets and create new opportunities, and our sustained growth and expertise in industries like real estate, entertainment and media, private equity and venture capital, and high-tech help build sustainable businesses and expand our associates’ potential for career advancement.
Headquartered in California, East West Bank (Nasdaq: EWBC) is a top performing commercial bank with an exclusive focus on the U.S. and Greater China markets. With a strong foundation, enterprising spirit and a commitment to absolute integrity, East West Bank gives people the confidence to reach further.
Overview:
The Data Scientist works closely with business partners and the Business Intelligence Team to turn data into critical information and knowledge that can be used to make sound business decisions. This individual must be able to analyze large amounts of raw and structured information to find patterns that will help our company. We will rely on you to build data products to extract valuable business insights.
In this role, you should be highly analytical with a knack for analysis, math and statistics. Critical thinking and problem-solving skills are essential for interpreting data. We also want to see a passion for machine-learning and research.
Responsibilities:
• Responsible for complex data mining efforts to discover patterns in large sets of data.
• Work closely with business partners and conduct analyses to translate data into actionable analytical solutions and promote information-based decision-making recommendations.
• Conduct POC, design and create an information foundation with the purpose of developing analytical solutions and predictive modeling.
• Incorporate machine learning, statistical modeling, visualization and analytics tools and data sources into the development of processes and techniques to use data effectively and efficiently.
• Communicate results and ideas to key decision makers using data visualization techniques
• Coordinate and conduct the tuning and optimization of the various financial AML models based on the methodology established. Make recommendations to improve financial monitoring through the development of new risk models, statistical analysis of model thresholds, and other sensitivity and productivity analyses.
• Generate, monitor and update machine learning models used to identify suspicious activity or enhance productivity. Work with AML teams to identify new models to assist in the identification of suspicious behavior or to enhance productivity.
• Use advanced statistical methods like clustering and regression analysis to ensure appropriate rigor around optimization processes.
• Conceptualize and develop new rules/models/scenarios, in coordination with AML subject matter experts, to address emerging trends and red flags.
• Ensure sound risk coverage, adequate quantitative model assessment and validation, and data quality completeness and integrity.
• Develop data-driven insights and communicate these effectively to management and diverse stakeholders, including management and regulators, using visualization techniques to showcase the results of analysis in concise presentations.
• Support the AML Group's periodic risk assessments through the analysis of data elements related to potential indicators of customer, product, or geographic risk, evaluating and enhancing the Group's risk rating methodologies, and identifying new quantitative factors that can be incorporated into the risk assessment process.
• Support Model Risk Management's model validation efforts to ensure models are performing as intended.
• Keep up-to-date with latest technology trends
Qualifications:
• Proven experience as a Data Scientist
• 2+ years hands on experience in Machine Learning or advance analytics
• MS in Computer Science / Statistics / Operations Research / Business Analytics or equivalent combination of skills, experience and education
• Banking product experience
• Analytical mind and business acumen
• Experience using business intelligence tools (e.g. Power BI) and data frameworks (e.g. Hadoop)
• Able to understand various data structures and common methods in data transformation
• Creative problem solver who thrives when presented with a challenge
• Excellent pattern recognition and predictive modeling skills
• Experience with programming languages such as Python, R, .NET C#
• Excellent attention to detail
• Able to multitask, prioritize, and manage time effectively
• Excellent communication, presentation, interpersonal and organizational skills
Desired
• Experience with DevOps, Continuous Integration and Continuous Delivery (Maven, Jenkins, Stash, Ansible, Docker) is a plus
• Azure Databricks, Machine Learning Studio and ONNX
• Software language - C#, Power Shell
• Experience working in Agile development environment